The full list, and the receipts.
The homepage carries the short version. This page carries the full list, the measured findings behind the advice, and where I have spoken.
Systems that shipped, and what they cost.
Foreman
Foreman keeps AI-written software honest. A feature passes three gates only I sign, and an agent does the work in a sealed room: a hard cap on attempts, escalate instead of guess. The process is public. The judgment stays private, because that is the part nobody can copy.
Flow · Sprint · Expertise PacksDataStream Intelligence
A sustainability benchmarking engine on public emission registers: 8 national PRTRs, 4.8 million rows, row-level lineage, running in Azure. The hard part is not the pipeline, it is entity resolution: plants are named after sites, companies after legal entities, and nothing joins for free. The data has a hard ceiling, and that finding is worth more than the product would have been.
Azure SQL · Python · Public registersOperator toolkit
The small tools that keep a one-person company honest. BurnRate measures real token spend from session logs: 95-98 percent of input was cached context, not fresh work. Voice-driven Time Registration turns spoken sessions into an audit-grade hour log. SentinelPR and ReleaseScribe, two open-source GitHub Actions, round out the drawer.
Python · JSON stores · SQLCipherZND OS
The control plane that runs the company: project state, deadlines and health live in plain git-versioned files with one JSON read-model on top, and every front-end is swappable. The local voice assistant (wake word to tool execution in under 2 seconds on an RTX 4060) is just one surface. Proved portable the hard way: the whole tree changed machines and AI subscriptions in one afternoon, nothing lost.
Files as source of truth · LangGraph voice surface · JSON read-modelCIPHER
A daily AI-accountability content brand. n8n on Hetzner, Claude for copy, HeyGen for video, the Meta Graph API for publishing. Ships every day. The lesson: LLM dedup is harder than it sounds at scale.
n8n · Hetzner · Meta Graph APIA-INSIGHTS / Valona platform
As Director of Architecture and Software Engineering, took a Competitive Market Intelligence platform from a Gmail inbox and a spreadsheet to a six-layer, multi-tenant SaaS product serving hundreds of enterprise customers, engineering team from 2 to 28 over eight years without accumulating legacy. Now Valona Intelligence, a Leader in the 2026 Gartner® Magic Quadrant™ for Competitive and Market Intelligence Platforms. The hard part at that scale is not features; it is keeping a growing system legacy-free while it ships.
Multi-tenant SaaS · Six-layer architecture · Gartner LeaderDamen Digital
A solo big-data and IoT initiative at Damen Shipyards became a CIO-sponsored, 30-person program ingesting vessel telemetry for fleet-wide monitoring, and then its own business unit. The hard part was never the sensors; it was making telemetry from hundreds of vessel types mean the same thing before anyone trusted a dashboard built on it.
IoT telemetry · Big data · Fleet monitoringNumbers I took myself.
Measured 85-98% of token spend in long agentic sessions was overhead, then cut it with concrete session-management fixes.
Built a multi-country emissions data pipeline: eight national registers plus the EU-wide E-PRTR, 4.8 million verified rows with row-level lineage.
Run the company on a portable file-based control plane; a voice agent on an 8 GB laptop GPU is one of its surfaces. Moved the whole tree across machines and AI subscriptions in an afternoon, nothing lost.
Cut design-review time by roughly 84% with a self-tested expertise agent, and threw out its perfect self-test score after auditing the test itself.
Let an agent take a data-pipeline change from spec to merged PR overnight, 73 tests green, while humans kept push, merge and declare-done.
Signed the last gate of Foreman's own build from a phone, and the harness correctly refused a reply that arrived outside the gate thread.
A checklist question written from a Python bug caught a same-class TypeScript bug in a different project, 17 days later.
Invited speaker at the 4th Thisworkz meetup (October 2024), the knowledge-sharing event of a six-company Dutch engineering collective: a session on using AI for data platforms, for a cross-company engineering audience. See the event post →
Available for talks and conference sessions on Agentic AI and data foundations. First-hand material and real numbers, no vendor slides. New sessions are added here as they happen.